New Research Reveals Overcoming Legacy Tech Issues Key to AI Success

Summary

An IDC survey of 1,400 organizations across eight Asia/Pacific markets reveals that legacy architectures and accumulated data debt severely hinder enterprise artificial intelligence initiatives. While 43% of surveyed organizations cite legacy systems as a major obstacle to application development, 95% report project delays and 90% have experienced failed modernization attempts. In contrast, high-performing organizations treat modernization as a continuous discipline across people, processes, and cloud-centric data platforms capable of processing both structured and unstructured workloads. These leading enterprises achieve nearly three times more digital revenue growth than peers still constrained by technical debt. IDC notes that addressing technical and data debt proactively avoids escalating AI failure rates and delivers superior return on investment compared to superficial lift-and-shift migrations.

Context

Organizations across Asia/Pacific pursuing artificial intelligence face significant barriers caused by legacy architectures, technical debt, and data debt. In an IDC survey across eight regional markets, 43% of organizations identified existing architectures as a major obstacle, 95% reported project delays, and one-third still relied on legacy relational databases unsuitable for high-volume, real-time AI demands.

Approach / What changed

IDC recommends adopting a continuous, multi-pronged modernization strategy encompassing people, processes, and technology. This includes moving beyond lift-and-shift migrations to cloud-native, cloud-centric data platforms that handle both structured and unstructured data, while aligning executive support, funding, and modern developer skills with transformation goals.

Takeaways

• IDC predicts that CIOs who fail to launch data debt remediation initiatives will face 50% higher AI failure rates and rising operational costs by 2027.
• Organizations in the Leaders cohort that embed continuous modernization into operations generate nearly three times more digital revenue than mainstream peers.
• Full application rewrites and database modernization require greater upfront investment than lift-and-shift migrations but can deliver up to three times the long-term benefit.

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